Methodology — National Benchmark of U.S. Mothers

How we conduct the Benchmark.

Wave 1 — May 2026
Download the public methodology (PDF)

About This Page

The National Benchmark of U.S. Mothers is a semiannual, nationally representative research infrastructure. Each of its five composite indices measures a condition mothers have identified as directly shaping their family's ability to thrive, so the institutions shaping those conditions can see what families actually need, trust, and prioritize. This page documents the complete methodology for Wave 1. It is published before data collection begins and updated with exact fieldwork dates after the survey closes.

Count on Mothers publishes full methodology with every wave, not as a compliance exercise, but because the integrity of independent research depends on it.

Wave 1 — Key Specifications

Survey population
Mothers with children under 18 in the United States
Total respondents (raw)
3,499
Analysis sample
2,818 mothers (80.5% of raw respondents)
Data collection
Wave 1, May 2026
Weighting method
Iterative raking (post-stratification)
Weighting sources
CPS 2023 ASEC Table A3; CPS 2024 ASEC HINC-04
Weighting dimensions
Age, race/ethnicity, household income, education, Census region
Design effect (DEFF)
1.496
Effective n
1,884
Margin of error
±2.3 percentage points at 95% confidence (full sample)
Weight trimming
[0.3, 3.0] per AAPOR convention

1. Sample Sourcing & Recruitment

Wave 1 draws from two panels, combined into a single weighted dataset. A probability-based national panel provides the representative core of the sample. The Count, CoM's community panel, adds engagement and community context. Both are weighted to Census benchmarks.
National Panel
A third-party online panel provider recruits a random, nationally representative sample of U.S. mothers. These respondents are recruited independently of CoM's community and are not self-selected into any CoM relationship. This panel is the primary source for Wave 1's representative quantitative sample.

Recruitment method

Vendor-sourced online panel. Respondents are screened at intake to confirm U.S. residency and current parenting status.

Compensation

Panel respondents receive a standard panel incentive.

Role in Wave 1

Provides the nationally representative random sample required for benchmark-grade findings.

Target n

Approximately 2,000 to 2,500 completed responses, sufficient for national topline reporting and key subgroup analysis.

Community Panel — The Count

The Count is CoM's subscriber community, mothers across all 50 states who joined countonmothers.org and opted in to participate in surveys. Wave 1 invitations are issued by direct email and through CoM's Anchor Mom Advisor network.

Recruitment method

Direct email invitation to The Count subscriber list, and personalized invitation to Anchor Mom Advisors, a structured advisory segment representing all U.S. regions and the political spectrum.

Respondent profile

Opt-in members of CoM's community. Contributes qualitative depth and higher response completeness than cold opt-in panels.

Role in Wave 1

Contributes qualitative depth and community-sourced context. Valid responses are incorporated into the weighted dataset, with post-survey weighting on Census benchmarks. See Blended Panel Weighting below.

Blended Panel Weighting

Both panels contribute eligible responses to a single Wave 1 analytic dataset. After data-quality review and integration, post-stratification raking is applied to the combined dataset to align the final sample with U.S. population benchmarks for mothers. This approach preserves the scale and demographic coverage of the national panel while incorporating the engagement and community coverage of The Count. All reported topline statistics and index scores are derived from the combined, weighted dataset.

Of 3,499 total respondents, 2,818 (80.5%) were retained for the final analysis sample after excluding non-mothers, flagged responses, and records missing required weighting variables. Approximately 88% of retained responses came from the national panel and 12% from The Count. The final weighted sample carries a margin of error of ±2.3 points.

Data quality

Responses are screened for quality across both panels. The probability-based panel provider applies attention checks and duplicate detection, and all open-ended responses are reviewed to flag fraudulent or AI-generated submissions.

2. Weighting Variables, Census Vintage & Method

Weighting Method

Post-stratification raking (iterative proportional fitting) is applied to the combined analytic dataset to align the final survey sample with U.S. population targets for mothers. Raking iteratively adjusts respondent weights across multiple demographic variables simultaneously until the sample distribution converges with population benchmarks. This is the standard approach used by major survey organizations including Pew Research Center, Gallup, and NORC at the University of Chicago.

Population Sources

Population targets are drawn from the following sources, each restricted to the relevant population of U.S. mothers or households with children:

Variable

Source

Target Population

Age
CPS 2023 ASEC Table A3
Mothers with children under 18
Race/Ethnicity
CPS 2023 ASEC Table A3
Mothers with children under 18
Household Income
CPS 2024 ASEC HINC-04
Households with children under 18
Education
CPS 2023 ASEC Table A3
Mothers with children under 18
Census Region
CPS 2023 ASEC Table A3
Households with children under 18
CPS = Current Population Survey (U.S. Census Bureau). ASEC = Annual Social and Economic Supplement.
‍
U.S. Census Bureau, Current Population Survey, 2023 Annual Social and Economic Supplement. Table A3: Parents With Coresident Children Under 18, by Living Arrangement, Sex, and Selected Characteristics: 2023.

Weighting Variables

The following variables are used as weighting targets. All targets are specific to U.S. mothers (not the general population):

Variable

Target Categories

Age
18–24, 25–34, 35–44, 45–54, 55+
Race/Ethnicity
Non-Hispanic White, Hispanic, Non-Hispanic Black, Non-Hispanic Asian, Non-Hispanic Other/Multiracial
Household Income
Less than $25,000 | $25,000–$49,999 | $50,000–$74,999 | $75,000–$99,999 | $100,000–$149,999 | $150,000–$199,999 | $200,000 or more
Education
Less than high school | High school diploma/GED | Some college, no degree | Associate degree | Bachelor's degree | Graduate or professional degree
Census Region
Northeast, Midwest, South, West
Weight Trimming: Raw raking weights are trimmed to the range [0.3, 3.0] per AAPOR convention before final application. Weight trimming prevents extreme weights from unduly distorting estimates while preserving population alignment. Sensitivity checks confirm that trimming does not materially alter topline results or subgroup patterns.

3. Margin of Error

All margins of error are reported at the 95% confidence level.

Sample

Margin of Error (±, 95% CI)

Full sample (n = 2,818)
±2.3 percentage points

4. Effective Sample Size

Effective sample size (n_eff) is reported alongside unweighted n for all wave publications and institutional deliverables.

Post-stratification weighting improves the demographic alignment of the sample but introduces design effects: some respondents receive larger weights than others, reducing statistical precision relative to a simple random sample of the same size. Effective sample size accounts for this reduction in precision and is calculated as:
n_eff = n / DEFF
Where DEFF represents the design effect introduced through weighting. Wave 1 achieved a DEFF of 1.496, yielding an effective sample size of 1,884. This is within the expected range of 1.2–1.5 for surveys of this design and indicates stable, well-calibrated weighting.

Unweighted n

Design Effect (DEFF)

Effective n

2,818
1.496
1,884
Effective sample size is reported in the methodology appendix of every wave report.

5. Index Construction

The National Benchmark tracks five composite indices, each scored on a 0–100 scale. For all five indices:  lower scores indicate better conditions (lower stress, lower financial strain, stronger trust, safer environment). This directional convention is held constant across all waves. 

Each index is constructed from a defined set of fixed survey items. Raw item responses are standardized, directionally aligned, and aggregated into a composite score using weighted averaging. Individual item weights within each index are documented in the methodology appendix and held constant across waves. 

The Five Indices

Each index measures a condition mothers have identified as directly shaping their family's ability to thrive. The Benchmark tracks all five over time — so the institutions shaping those conditions can see what families actually need, trust, and want.

Acronym

Index Name

What It Measures

MCSI
Maternal Capacity & Stress Index
Perceived stress, time scarcity, and the cognitive, emotional, and physical strain of daily life. MCSI tracks maternal stress and capacity as a standing condition of family life, one mothers consistently name as directly shaping their family's ability to thrive.
FEPI
Family Economic Pressure Index
Household financial strain, childcare and work constraint, and healthcare affordability. Treats economic pressure as a persistent condition rather than an income threshold — capturing the squeeze families feel regardless of nominal income level.
ITAI
Institutional Trust & Accountability Index
Institutional distrust and accountability gaps as experienced by mothers across schools, healthcare systems, technology platforms, and government.
YECCI
Youth Environment & Commercial Conditions Index
AI and digital engagement among children, online platform and content risk, advertising and harmful-product marketing, neighborhood safety, and outdoor and green-space access. Captures the digital, commercial, and physical environments children are embedded in, and mothers' assessment of whether safeguards are adequate.
CWASI
Child Wellbeing Access & Support Index
Barriers to child mental health access, school support deficits, and the navigation friction families encounter when seeking services, including insurance barriers, provider shortages, and out-of-pocket costs. Also captures protective factors in the child's social ecology, such as peer friendship quality.
Each index measures a condition mothers have identified as directly shaping their family's ability to thrive. The Benchmark tracks all five over time, so the institutions shaping those conditions can see what families actually need, trust, and want.

6. Panel Integrity Protocols

As AI-generated and bot-produced survey responses become a growing threat to online panel quality industry-wide, Count on Mothers treats panel integrity as a quality control step. The following protocols are applied to every wave.

Open-Ended Response Quality Control

Wave 1 includes at least one open-ended response question. All open-ended responses are screened for: (a) copy-paste duplication across respondents and (b) off topic or nonsensical content.
Responses failing this screen are removed from the dataset. The open ended QC step provides a high-sensitivity signal for detecting synthetic respondents that closed-ended items alone cannot detect.

Community Panel Longitudinal Integrity

The Count community panel has structural integrity advantages over cold opt-in panels. Community  members have established relationships with CoM over time, creating behavioral fingerprints that enable anomaly detection. Longitudinal wave-over-wave participation patterns are monitored for irregular activity. New community panel entrants for Wave 1 are subject to the same speed, open-ended, and attention  check protocols as the paid panel respondents.

Why Panel Integrity Matters

The methodological risk of AI-contaminated survey panels is not theoretical — it is actively degrading the quality of opt-in panel research industry-wide. Count on Mothers’ blended panel architecture, combined with multi-layer integrity screening, produces a more defensible dataset than single-source cold panels. We document and publish these protocols so that anyone evaluating the research, including institutional partners and journalists, can assess its integrity.

7. Instrument Stability

Wave 1 establishes the baseline. It is the foundation from which all trend analysis is built.

One wave = report.
Two waves = trend.
Three waves = infrastructure.

The Wave 1 core instrument consists of 25–35 fixed questions. These questions are held constant across waves. The stability of the core instrument is what makes longitudinal comparison possible — and what makes the Benchmark's value compound with each subsequent wave.
  • Fixed core questions: Do not change across waves without a documented rationale, a formal review by the research team and Methodology Advisory Board, and an overlap procedure (running both old and new wording in the transition wave on split samples) to establish trend continuity before retiring any item.
  • Response scales: Held constant within subdomains. Mixing scale types across waves introduces measurement error.
  • Index construction: Item composition and weighting within each index is documented and locked at Wave 1. Changes to index construction require the same overlap procedure as item changes.

Rotating Modules

Wave 1 includes a supplemental rotating module. Rotating module questions address time-sensitive topics and are positioned after the fixed core instrument. They are clearly labeled as supplemental in all published materials.
  • Independence from core scores: Rotating module responses are not incorporated into the five composite index scores. They are analyzed and reported separately.
  • Labeling: All findings from the rotating module are labeled "Supplemental, Wave [n] Rotating Module" in published materials and data deliverables.
  • Institutional add-on: Rotating module topic selection is eligible for institutional underwriting as an add-on. The CoM research team retains final authority over question wording, framing, and inclusion.

8. Research Team

Every wave report and institutional deliverable displays the research team's credentials prominently, so the expertise behind each finding is transparent to any reader.
Jennifer Brailsford, PhD
Director of Research
Survey methodology and research design. Responsible for instrument architecture, question development, index construction, and methodology documentation.
Melissa Lawrence, MPH, MS
Director of Data Science
Statistical weighting, data cleaning, and quantitative analysis. Responsible for raking procedures, effective sample size calculation, and longitudinal dataset architecture.
Academic partnerships supporting Wave 1 methodology:

Count on Mothers collaborates with University College London researchers Kaitlyn Regehr PhD, Photini Vrikki PhD, and Katharine Smales PhD on instrument design, question framing, and review of preliminary findings. CoM retains final authority over all methodology and findings.

9. Fieldwork Dates

Wave 1 Field Dates

Survey open:
may 7, 2026
Survey close:
may 27, 2026

10. Sample Growth & Longitudinal Transparency

The Benchmark is designed to grow in analytical power across waves.

Wave

Target n

Approx. MOE (95% CI)

Wave 1 (May 2026)
2,818
±2.3 pp
Wave 2+
Growing as community panel expands
Decreasing with scale
As the CoM community panel grows through ongoing subscriber recruitment, subsequent waves will increase sample size, reducing margin of error and enabling more granular subgroup analysis at the regional, demographic, and political levels. This growth is a designed feature of the Benchmark architecture, not a concession. The paid panel provides a stable representativeness floor at any sample size. Community panel growth compounds the dataset's analytical power without replacing the statistical rigor of the random sample foundation.
Wave-over-wave sample sizes and methodology changes are documented in a public change log maintained on this page. No change to core instrument questions, index construction, or weighting methodology is made without a formal overlap procedure and published rationale.

Questions about our methodology?

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Count on Mothers • National Benchmark of U.S. Mothers • Wave 1 Methodology • May 2026
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National Benchmark of U.S. Mothers
Wave 1 Methodology • May 2026